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At least 1,099 records · Page 61

Fecal microbiota transplantation ameliorates type 2 diabetes via metabolic remodeling of the gut microbiota in db/db mice

Gut microbiome (GM) deregulation has been implicated in major conditions such as obesity and type 2 diabetes (T2DM). Our previous prospective study indicated that fecal microbiota transplantation (FMT) successfully improved patients with T2DM. We hypothesized that FMT may be a potential therapeutic method for T2DM, but its precise mechanisms in T2DM remains to be elucidated. Eight db/m mice were FMT donors and control mice, and 16 genetically diabetic db/db mice were equally divided into two groups (db/db+phosphate-buffered saline (PBS) group, db/db+FMT group). The db/db+FMT group was administered fresh fecal suspension (0.2 mL/mice) daily for 4 weeks. Analysis of the GM and serum metabolome was carried out by 16S ribosomal RNA sequencing and liquid chromatogram-mass spectrometry, respectively. Effects of FMT on the gut barrier and pancreas were assessed using protein assays, messenger RNA, immunohistology and clinical indicators testing. Our results showed that FMT treatment of db/db mice relieves a series of clinical indicators, including fasting plasma glucose, serum insulin and oral glucose tolerance test among others. Compared with non-diabetic control mice, db/db+PBS mice exhibited decreased abundance of Ruminococaceae, Porphyromonadaceae and increased abundance of Rikenellaceae and Lactobacillaceae. FMT treatment reversed this effect on the microbiome. Eleven metabolites were changed between the db/db+PBS and db/db+FMT groups. Correlation analysis showed that the structural changes of the GM were correlated with host metabolite levels. We further showed that FMT treatment of db/db mice improved intestinal barrier function, reduced inflammation and caused an alteration in the number of circulating immune cells. FMT-mediated changes in the GM, serum metabolites, intestinal epithelial barrier, inflammation and circulating immune cells play an important role in the efficacy of FMT on T2DM disease progression.

60 APPLIED LIFE SCIENCES↗

Metabolic engineering of the oleaginous yeast Yarrowia lipolytica PO1f for production of erythritol from glycerol

Abstract Background Sugar alcohols are widely used as low-calorie sweeteners in the food and pharmaceutical industries. They can also be transformed into platform chemicals. Yarrowia lipolytica , an oleaginous yeast, is a promising host for producing many sugar alcohols. In this work, we tested whether heterologous expression of a recently identified sugar alcohol phosphatase (PYP) from Saccharomyces cerevisiae would increase sugar alcohol production in Y. lipolytica . Results Y. lipolytica was found natively to produce erythritol, mannitol, and arabitol during growth on glucose, fructose, mannose, and glycerol. Osmotic stress is known to increase sugar alcohol production, and was found to significantly increase erythritol production during growth on glycerol. To better understand erythritol production from glycerol, since it was the most promising sugar alcohol, we measured the expression of key genes and intracellular metabolites. Osmotic stress increased the expression of several key genes in the glycerol catabolic pathway and the pentose phosphate pathway. Analysis of intracellular metabolites revealed that amino acids, sugar alcohols, and polyamines are produced at higher levels in response to osmotic stress. Heterologous overexpression of the sugar alcohol phosphatase increased erythritol production and glycerol utilization in Y. lipolytica . We further increased erythritol production by increasing the expression of native glycerol kinase (GK), and transketolase (TKL). This strain was able to produce 27.5 ± 0.7 g/L erythritol from glycerol during batch growth and 58.8 ± 1.68 g/L erythritol during fed-batch growth in shake-flasks experiments. In addition, the glycerol utilization was increased by 2.5-fold. We were also able to demonstrate that this strain efficiently produces erythritol from crude glycerol, a major byproduct of the biodiesel production. Conclusions We demonstrated the application of a promising enzyme for increasing erythritol production in Y. lipolytica . We were further able to boost production by combining the expression of this enzyme with other approaches known to increase erythritol production in Y. lipolytica . This suggest that this new enzyme provides an orthogonal route for boosting production and can be stacked with existing designs known to increase sugar alcohol production in yeast such as Y. lipolytica . Collectively, this work establishes a new route for increasing sugar alcohol production and further develops Y. lipolytica as a promising host for erythritol production from cheap substrates such as glycerol.

09 BIOMASS FUELS↗

S. elongatus PCC 7942 Carbon Metabolism Proteomics (MC-DP2)

The purpose of this experiment was to examine the redox proteome of S. elongatus PCC 7942 CscB/SPS under different light conditions (light and dark) and culture conditions (dense and dilute optical density). Samples were processed using a resin-assisted capture (RAC) workflow with TMT labeling to enrich and quantify protein cysteines which were differentially oxidized under four conditions. The datasets were generated by a Q Exactive Plus Orbitrap Mass Spectrometer coupled with a Waters nanoAcquity UPLC, then searched by MSGF+ for downstream redox PTM analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Multiomics Data Collection, Visualization, and Utilization for Guiding Metabolic Engineering

Biology has changed radically in the past two decades, growing from a purely descriptive science into also a design science. The availability of tools that enable the precise modification of cells, as well as the ability to collect large amounts of multimodal data, open the possibility of sophisticated bioengineering to produce fuels, specialty and commodity chemicals, materials, and other renewable bioproducts. However, despite new tools and exponentially increasing data volumes, synthetic biology cannot yet fulfill its true potential due to our inability to predict the behavior of biological systems. Here, we showcase a set of computational tools that, combined, provide the ability to store, visualize, and leverage multiomics data to predict the outcome of bioengineering efforts. We show how to upload, visualize, and output multiomics data, as well as strain information, into online repositories for several isoprenol-producing strain designs. We then use these data to train machine learning algorithms that recommend new strain designs that are correctly predicted to improve isoprenol production by 23%. This demonstration is done by using synthetic data, as provided by a novel library, that can produce credible multiomics data for testing algorithms and computational tools. In short, this paper provides a step-by-step tutorial to leverage these computational tools to improve production in bioengineered strains.

09 BIOMASS FUELS↗

Editorial: Synthetic metabolism for the third-generation (3G) biorefineries

The demand for energy has increased significantly to meet the development of the economy and the increasing population. With the continuous consumption of energy, the shortage of non-renewable resources and the greenhouse effect have aroused worldwide attention. Therefore, the conversion of one-carbon substrates such as formate, methanol, and carbon dioxide (CO 2 ) as sustainable feedstocks into high-value-added products is a potential way to address such concerns. Although one-carbon substrates can be converted into organics by natural pathways, these pathways may not be optimal due to the multiple enzymes involved and remarkable amounts of energy consumption. Thus, synthetic biology, as an emerging field, offers a new approach to boost one-carbon bioconversion.

09 BIOMASS FUELS↗

A Long Non-coding RNA, LOC157273, Is an Effector Transcript at the Chromosome 8p23.1-PPP1R3B Metabolic Traits and Type 2 Diabetes Risk Locus

Causal transcripts at genomic loci associated with type 2 diabetes (T2D) are mostly unknown. The chr8p23.1 variant rs4841132, associated with an insulin-resistant diabetes risk phenotype, lies in the second exon of a long non-coding RNA (lncRNA) gene, LOC157273, located 175 kilobases from PPP1R3B, which encodes a key protein regulating insulin-mediated hepatic glycogen storage in humans. We hypothesized that LOC157273 regulates expression of PPP1R3B in human hepatocytes. We tested our hypothesis using Stellaris fluorescent in situ hybridization to assess subcellular localization of LOC157273; small interfering RNA (siRNA) knockdown of LOC157273, followed by RT-PCR to quantify LOC157273 and PPP1R3B expression; RNA-seq to quantify the whole-transcriptome gene expression response to LOC157273 knockdown; and an insulin-stimulated assay to measure hepatocyte glycogen deposition before and after knockdown. We found that siRNA knockdown decreased LOC157273 transcript levels by approximately 80%, increased PPP1R3B mRNA levels by 1.7-fold, and increased glycogen deposition by >50% in primary human hepatocytes. An A/G heterozygous carrier (vs. three G/G carriers) had reduced LOC157273 abundance due to reduced transcription of the A allele and increased PPP1R3B expression and glycogen deposition. We show that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and a causal transcript at an insulin-resistant T2D risk locus.

59 BASIC BIOLOGICAL SCIENCES↗

Kinetics of organic transformations under mild aqueous conditions: implications for the origin of life and its metabolism

The rates of thermal transformation of organic molecules containing carbon, hydrogen, and oxygen were systematically examined in order to identify the kinetic constraints that governed origin-of-life organic chemistry under mild aqueous conditions. Arrhenius plots of the kinetic data were used to estimate the reaction of half-lifes at 50 degrees C. This survey showed that hydrocarbons and organic substances containing a single oxygenated group were kinetically the most stable; whereas organic substances containing two oxygenated groups in which one group was an alpha- or beta-positioned carbonyl group were the most reactive. Compounds with an alpha- or beta-positioned carbonyl group (aldehyde or ketone) had rates of reaction that were up to 10(24)-times faster than rates of similar molecules lacking the carbonyl group. This survey of organic reactivity, together with estimates of the molecular containment properties of lipid vesicles and liquid spherules, indicates that an origins process in a small domain that used C,H,O-intermediates had to be catalytic and use the most reactive organic molecules to prevent escape of its reaction intermediates.

Biogenesis↗

Respiration regimes in rivers: Partitioning source–specific respiration from metabolism time series

Respiration in streams is controlled by the timing, magnitude, and quality of organic matter (OM) inputs from internal primary production and external fluxes. Here, we estimated the contribution of different OM sources to seasonal, annual, and event-driven characteristics of whole-stream ecosystem respiration (ER) using an inverse modeling framework that accounts for possible time-lags between OM inputs and respiration. We modeled site-specific, dynamic OM stocks contributing to ER: autochthonous OM from gross primary production (GPP); allochthonous OM delivered during flow events; and seasonal pulses of leaf litter. OM stored in the sediment and dissolved organic matter (DOM) transported during baseflow were modeled as a stable stock contributing to baseline respiration. We applied this modeling framework to five streams with different catchment size, climate, and canopy cover, where multi-year time series of ER and environmental variables were available. Overall, the model explained between 53% and 74% of observed ER dynamics. Respiration of autochthonous OM tracked seasonal peaks in GPP in spring or summer. Increases in ER were often associated with high-flow events. Respiration associated with litter inputs was larger in smaller streams. Time lags between leaf inputs and respiration were longer than for other OM sources, likely due to lower biological reactivity. Model estimates of source-specific ER and OM stocks compared well with existing measures of OM stocks, inputs, and respiration or decomposition. Our modeling approach has the potential to expand the scale of comparative analyses of OM dynamics within and among freshwater ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗